Update modules/ui.py

modules/ui.py

@@ -171,35 +171,35 @@ def display_student_progress(username, lang_code='es'):
     st.title(f"Progreso de {username}")
 
     if student_data['word_count']:
-            st.subheader("Total de palabras por categoria gramatical")
-            
-            df = pd.DataFrame(list(student_data['word_count'].items()), columns=['category', 'count'])
-            df['label'] = df.apply(lambda x: f"{POS_TRANSLATIONS[lang_code].get(x['category'], x['category'])}\n({x['count']})", axis=1)
-            
-            fig, ax = plt.subplots(figsize=(8, 6), dpi=100)  # Tamaño reducido
-            colors = [POS_COLORS.get(cat, '#CCCCCC') for cat in df['category']]
-            
-            squarify.plot(sizes=df['count'], label=df['label'], color=colors, alpha=0.8, ax=ax)
-            
-            for text in ax.texts:
-                text.set_visible(False)
-            
-            norm = plt.Normalize(df['count'].min(), df['count'].max())
-            for rect, label in zip(ax.patches, df['label']):
-                x = rect.get_x() + rect.get_width()/2
-                y = rect.get_y() + rect.get_height()/2
-                size = norm(rect.get_height() * rect.get_width())
-                ax.text(x, y, label, ha='center', va='center', fontsize=6+size*8)  # Tamaño de fuente reducido
-            
-            plt.title('Treemap del total de palabras por categoria gramátical')
-            plt.axis('off')
-            
-            buf = io.BytesIO()
-            fig.savefig(buf, format='png')
-            buf.seek(0)
-            st.image(buf, use_column_width=True)
-        else:
-            st.info("No hay datos de conteo de palabras disponibles.")
+        st.subheader("Total de palabras por categoria gramatical")
+        
+        df = pd.DataFrame(list(student_data['word_count'].items()), columns=['category', 'count'])
+        df['label'] = df.apply(lambda x: f"{POS_TRANSLATIONS[lang_code].get(x['category'], x['category'])}\n({x['count']})", axis=1)
+        
+        fig, ax = plt.subplots(figsize=(8, 6), dpi=100)  # Tamaño reducido
+        colors = [POS_COLORS.get(cat, '#CCCCCC') for cat in df['category']]
+        
+        squarify.plot(sizes=df['count'], label=df['label'], color=colors, alpha=0.8, ax=ax)
+        
+        for text in ax.texts:
+            text.set_visible(False)
+        
+        norm = plt.Normalize(df['count'].min(), df['count'].max())
+        for rect, label in zip(ax.patches, df['label']):
+            x = rect.get_x() + rect.get_width()/2
+            y = rect.get_y() + rect.get_height()/2
+            size = norm(rect.get_height() * rect.get_width())
+            ax.text(x, y, label, ha='center', va='center', fontsize=6+size*8)  # Tamaño de fuente reducido
+        
+        plt.title('Treemap del total de palabras por categoria gramátical')
+        plt.axis('off')
+        
+        buf = io.BytesIO()
+        fig.savefig(buf, format='png')
+        buf.seek(0)
+        st.image(buf, use_column_width=True)
+    else:
+        st.info("No hay datos de conteo de palabras disponibles.")    
         
 ############################################# Diagramas de Arco (consolidados)#####################################################################3
         st.header("Diagramas de Arco")